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The effects of Korean wage hikes on Korean trade structures with the U.S. and Japan.

Input-Output Model," 1979 Proceedings of the Business and Economic Statistics Section. Washington D.C.: American Statistical Association, 1979, pp. 236-41.

8. ----- and ----- . "The Multicountry Industrial Linkage Model," Unpublished paper, Division of Economics, The University of Oklahoma, 1987.

9. ----- and -----, "Measuring the Development Impact of A Transportation System." Journal of Regional Science, Volume 25, May, 1985, 241-58.

10. ----- and -----, "Measuring the Effect of Cost Variation on Industrial Outputs." Journal of Regional Science, Volume 28, November 1988, 563-78.

I. Introduction

During the last two decades, Korea has experienced a rapid economic growth. This growth is primarily the results of two factors; (1) Korean outward development strategy, and (2) a high quality labor force working at a relatively low wage rate. Until 1985, Korean labor market conditions were conducive to the outward development strategy.

Before 1985, Korean workers were unable to negotiate their wage with employers through the usual channels of labor unions. As a substitute for labor unions, many Korean firms utilized worker-employer councils, which were a variant of unions. These councils gave a nominal capability of intermediating labor disputes and of accomplishing collective agreements between workers and employers. However, in many firms the leaders of these councils were nominated by employers. Indeed, these workers did not have any meaningful channel to negotiate their wages with employers.

Prior to 1985, wages in most small and mid-sized firms were determined by wage regulations which were set up by employers beforehand. In large firms such as conglomerates, the government issued guidelines for the percentile increase of each industrial wage with respect to macro-economic circumstances. Since the increase was typically determined at a much lower rate than the actual productivity growth, most large firms had no reason to deviate from these government guidelines. Furthermore, the National Security Special Law has been in force since 1972. This law specifically prohibited any collective action and collective wage bargaining.

With the recent political liberalization in 1985, including the correction of the National Security Special Law and various labor acts, Korean workers started demanding higher wages and insisting on the abolition of improper labor practices. Korean workers claimed their wages had been unfairly diminished by economic policy in comparison with their actual productivity.

This political liberalization was so abrupt that both workers and employers were ill-prepared for collective wage bargaining. There are several reasons(1) why massive labor disputes were protracted for such a long time. Both employers and workers stubbornly held to their strict positions in wage bargaining. Many employers stubbornly resisted the existence of the union itself. Some employers even announced publicly that firms would be shut down if workers formed any union or made any labor dispute. These employers' behavior mainly came from the absence of any past experience of collective bargaining. On the other hand, workers' wages had been suppressed at a low rate for past two decades. Once politically liberalized, the workers demanded much higher wages all at once. This approach was not acceptable to most employers, especially in such a short period. Second, both parties had such imperfect information about the other parties that they often failed to convey the true position of their strategic schedules to the other parties in negotiation. This imperfect information about the other parties were mainly due to the inexperience in wage bargaining.

The purpose of this paper is to trace the effects of wage hikes on Korean imports and exports with the United States and Japan. These two countries are the most important trade partners for Korea. This paper investigates the industrial effects of the rising wage rates on prices, outputs, and trade structures of Korea, Japan, and the United States.

In order to answer these questions, we construct a Multi-country Industrial Linkage (MIL) model of Korea, Japan, and the United States. The MIL model is an applied general equilibrium model which fully captures the profit maximizing behavior of industries and the utility maximizing behavior of consumers. The MIL model has an explicit linkage between the profit maximizing capital stocks and the demands for investment goods. It adopts CES production frontiers to describe the production technology of each industry in the country.

The MIL model is an extension of conventional input-output models [13], Leontief and Strout [6], Polenske [16], Miller and Blair [12], Richardson [15], Hewing and Jenson [3], and Rietveld [14] by permitting the model to capture the output effects of cost variations under the framework of multicountry input-output transactions which explicitly identify the origin and destination of each commodity as well as their final usages. There are many general equilibrium models which trace the output effects of cost variations such as Jorgenson [4], Shoven and Whalley [17] and Srinivasan and Whalley [18]. The import and export items are usually aggregated across all trading countries in order to report the effects of various trends on trade patterns. In these general equilibrium approaches, input-output coefficients were rarely reported. Hence, the trade flows of each commodity between countries could not be described nor the input transactions in industry and country detail could be identified. The MIL model enables us to identify the import and export of each product from its origin and destination to its final usages in the consuming country.

Following the introduction, section II describes the theoretical background of the MIL model. Section III presents a CES version of MIL model, and section IV provides a labor simulation model to trace the structural effects on Korean imports and exports with the United States and Japan. After a brief description of data used in this study, section V summarizes the empirical findings of the labor simulation. We could not gather the elasticity of substitution between inputs for Japan and Korean industries. Hence, the unitary elasticities of substitution for all industries (Cobb-Douglas function) are used for the empirical pan under the assumption that the industrial structures of Japan and Korea are similar to those of the United States.(2) Section VI offers brief concluding remarks.

II. The Theoretical Background of the Model

The Multicountry Industrial Linkage (MIL) model refers to a computable general equilibrium model which satisfies the following six conditions; (1) Producer Equilibrium Conditions, (2) Household Equilibrium Conditions, (3) Linkage between Investment and Capital Stocks, (4) Balancing Conditions, (5) Trade Flow Conditions, and (6) Resource Constraints. The model captures the profit maximizing behavior of firms and the utility maximizing behavior of households with given supply of resources in the regions. The model assumes that households interact with business firms by supplying primary inputs for firms to earn income which is used to spend for consumption.

Producer Equilibrium Conditions

It is assumed that the production technology of the region is described by a homogenous production frontier (i.e., a constant return to scale production technology). With given production frontiers (equation (1)) describing the production technology of the country, the profit maximizing input demands are defined by equations (2) and (3):

Production Frontiers

[Mathematical Expression Omitted]

where

[Mathematical Expression Omitted] = the amount of product i produced in country s and delivered to industry j in country r;

[Mathematical Expression Omitted] = the amount of primary input k employed by industry j in country r;

[Mathematical Expression Omitted] = the amount of product j produced by industry j in country r.

Profit Maximizing Input-Equations

Intermediate Inputs

[Mathematical Expression Omitted]

Primary Inputs

[Mathematical Expression Omitted]

where [Mathematical Expression Omitted], [Mathematical Expression Omitted], and [Mathematical Expression Omitted] are the producer price of [Mathematical Expression Omitted], the primary input price of [Mathematical Expression Omitted], and the purchase price of [Mathematical Expression Omitted] respectively.

Household Equilibrium Conditions

It is assumed that the household sector in region r has an Indirect Utility Function (equation (4)), from which a utility maximizing consumer demand equation (5) is derived by using Roy's Identity. The consumer budget is a constant fraction of the gross national products (i.e., the sum of values added as shown in equation (6)).

Indirect Utility Function

[Mathematical Expression Omitted]

Consumer Demand Equation

[Mathematical Expression Omitted]

Consumption Budget

[Mathematical Expression Omitted]

Linkage Between Capital Stock and Investment

The gross investment in the region [Mathematical Expression Omitted] is the sum of net investment and replacement investment. The net investment is a change in profit maximizing capital stock ([K.sup.r] - [K.sup.r](-1)) and the replacement investment is assumed to be a constant fraction of beginning capital stock in region r ([[Theta].sup.r][K.sup.r](-1)). Let the second primary input ([Mathematical Expression Omitted]) be capital stock. Then, [Mathematical Expression Omitted]. We further assume that the growth rate of capital stock is constant: i.e.,

[K.sup.r] - [K.sup.r](-1)/[K.sup.r](-1) = [n.sup.r]. (7)

Then, the gross investment in the region r has the following relation.

Gross Investment

[Mathematical Expression Omitted]

Note that [Phi][prime] = ([n.sup.r] + [[Theta].sup.r])/(1 + [n.sup.r]).

We further assume that the firms have the following indirect utility function and purchase their investment goods so as to maximize their utilities. By using Roy's Identity, the investment demand equation (10) is derived.

Indirect Utility Function of the Firms

[Mathematical Expression Omitted]

Investment Demand Equations

[Mathematical Expression Omitted]

Other Conditions

The model requires the balancing equations (11) which equate the supply of each product to the total demands for the product, the trade flow equations (12) which identify trade flow conditions of the economy, and the resource constraints of the regional economy which specify the maximum available primary input resources such as labor and capital.

Balancing Equations

[Mathematical Expression Omitted]

Trade Flow Equations

[Mathematical Expression Omitted]

Import Equations

[Mathematical Expression Omitted]

Export Equations

[Mathematical Expression Omitted]

Resource Constraints

[Mathematical Expression Omitted]

where

[Mathematical Expression Omitted] = all other final demands for product i in country r which is shipped from country s except consumption and investment:

[Mathematical Expression Omitted] = maximum available resource k in the country r;

[Mathematical Expression Omitted] = the import of commodity i by country r;

[Mathematical Expression Omitted] = the export of commodity i by country s.

Purchase Price and Delivery Cost Factor

It is assumed that the purchase price ([Mathematical Expression Omitted]) is a product of the trade cost factor ([Mathematical Expression Omitted] and the producer price of commodity i in region [Mathematical Expression Omitted]):

[Mathematical Expression Omitted].

The trade cost factor ([Mathematical Expression Omitted]) is all additional costs required to deliver commodity i from country s to r. It includes the transportation cost of delivering the commodity, tariffs or nontariff import restrictions imposed on the commodity, and the cost variation due to the change in exchange rate. For the further discussion of [Mathematical Expression Omitted].

The model with n industries, m countries, and h primary inputs has (2(nm + nmm + m) + nnmm + nmh) equations to solve the same number of unknowns ([Mathematical Expression Omitted], [Mathematical Expression Omitted], [Mathematical Expression Omitted], [Mathematical Expression Omitted], [Mathematical Expression Omitted]), with given transportation cost factors ([Mathematical Expression Omitted]), primary input prices ([Mathematical Expression Omitted]) and other final demands ([Mathematical Expression Omitted]).

The solution of this model is usually done by the following operations. The profit maximizing inputs ([Mathematical Expression Omitted]) are used in the production frontiers to derive the corresponding price frontiers. Note that [Mathematical Expression Omitted] is cancelled out in the operation because the production frontier is homogenous of degree zero in inputs and in output.

The profit maximizing intermediate and primary inputs (2 and 3), consumer demand equations (5), and investment equations (10) are used in the balancing equations (11) to obtain the output equations which determine industrial outputs ([Mathematical Expression Omitted]).

Given [Mathematical Expression Omitted] and [Mathematical Expression Omitted], the price frontiers solve the equilibrium prices independently from other equations. Then, by using the equilibrium prices obtained from the price frontiers, the output equations with given other final demands ([Mathematical Expression Omitted]) determine industrial outputs. These equilibrium prices and outputs determine all other endogenous variables (intermediate inputs, primary inputs, consumption, investment, and trade flows) of the model.

III. CES Version of the Model

In order to implement this model, the users should choose the functional forms of production frontiers (equation (1)) and the indirect utility functions of households (equation (4)) and business (equation (9)). When the users choose the functional forms, they should consider the following aspects: (1) the theoretical flexibility of the model; (2) the efforts needed to collect the data and to implement the model; (3) the computational burdens required to solve the model as the level of regional and industrial disaggregations becomes finer. If the users choose Translog functional forms [2], the model will be theoretically most defendable, but it will face the data collection problems and the severe computational burdens. The multiregional input-output transaction data are not available over a long period to give enough degrees of freedom for the Translog parameter estimation.

The earlier version of MIL model [8] adopts the Linear Logarithmic production frontiers. For this version, the CES production frontier is used. The Linear Logarithmic production function is a special case of the CES productions. For computational simplicity, we also adopt the Linear Logarithmic indirect utility functions for household and business sectors for this model.

Producer Sector

It is assumed that industrial output ([Mathematical Expression Omitted]) is produced by the following CES production frontiers:

[Mathematical Expression Omitted]

where [Mathematical Expression Omitted], [Mathematical Expression Omitted], [Mathematical Expression Omitted], and [Rho]rj are the parameters of the production frontiers which satisfy the following conditions:

[Mathematical Expression Omitted]

[Rho]rj [is greater than or equal to] -1. (19)

Using the profit maximizing conditions (2) and (3), we derive the following CES input demand equations:

[Mathematical Expression Omitted]

[Mathematical Expression Omitted].

Note that [Rho]rj is the elasticity of substitution between a pair of inputs for industry j in region r, i.e.,

[Rho]rj = 1/(1 + [Rho]rj). (22)

Household Sector

The Household Sector is assumed to have the following linear logarithmic indirect utility function:

[Mathematical Expression Omitted]

where [Mathematical Expression Omitted].

Using Roy's Identity, we derive the following utility maximizing consumer demand equations:

[Mathematical Expression Omitted]

where

[Mathematical Expression Omitted].

Note that [E.sup.r] is the aggregate consumption budget of region r.

Linkage Between Investment and Capital Stock

We further assume that the business sector has the following linear logarithmic indirect utility function to allocate investment expenditures:

[Mathematical Expression Omitted]

where [Mathematical Expression Omitted].

Using Roy's Identity, we derive the following utility maximizing investment demand equations:

[Mathematical Expression Omitted]

where

[Mathematical Expression Omitted].

Note that [Mathematical Expression Omitted] is the service price of capital stock and [Mathematical Expression Omitted] is the profit maximizing capital stock from (21).

Purchase Prices

The purchase prices ([Mathematical Expression Omitted]) in intermediate input equations (20), consumer demand equations (24), and investment demand equations (27) are replaced by the product of trade cost factor ([Mathematical Expression Omitted]) of shipping commodity i from country s to r and the producer price ([Mathematical Expression Omitted]) of the commodity i in country s, i.e.,

[Mathematical Expression Omitted].

This relation is already described in equation (14).

This CES version of the model can be solved by the following recursive solutions. First, the price block is solved. The prices obtained from the price block are used to solve the output block. The industrial outputs and equilibrium prices are then used to compute intermediate inputs, primary inputs, consumer demands, investment demands, aggregate consumption expenditures, and aggregate investment expenditures in each region.

Price Block

We use the profit maximizing input demands (equations (20) and (21)) to eliminate [Mathematical Expression Omitted] and [Mathematical Expression Omitted] in the production frontiers (equation (17)). Note that the industrial output ([Mathematical Expression Omitted]) is cancelled out in the process because of the homogeneity assumption in the production frontiers, and the CES price frontiers are obtained:(5)

[Mathematical Expression Omitted]

where

[Lambda]rj = [Rho]rj[Sigma]rj [Sigma]rj = 1/(1 + [Rho]rj)

Note that [Sigma]rj is the elasticity of substitution between a pair of inputs in industry j in region r. This price equation can be stacked as the following matrix form:

[Mathematical Expression Omitted]

where

[p.sup.[Lambda]] = an nm component vector of [Mathematical Expression Omitted];

[Mathematical Expression Omitted] = an nm component vector of [Mathematical Expression Omitted] for k = 1, ..., h;

S = an nm by nm matrix of [Mathematical Expression Omitted];

[V.sub.k] = an nm component diagonal matrix of [Mathematical Expression Omitted].

We notice that the equilibrium prices are linearly solved by (32). Given [Lambda]rj, all equilibrium prices ([Mathematical Expression Omitted]) are determined.

[Mathematical Expression Omitted]

Output Block

The consumer budget equations (25) and the profit maximizing primary input equation (21) are combined to the consumer demand equations (24) to derive the following equations:

[Mathematical Expression Omitted].

The investment budget equations (28) and the profit maximizing capital input equation ((31) when k = 2) are combined to the investment demand equations (27) to derive the following equations:

[Mathematical Expression Omitted].

The model assumes that the output i produced by country [Mathematical Expression Omitted] is demanded by business sectors as intermediate inputs, ([Mathematical Expression Omitted]) or investment demands ([Mathematical Expression Omitted]), by households as consumer demands ([Mathematical Expression Omitted]), and by other users as other final demands ([Mathematical Expression Omitted]) as shown in the following balancing equations:

[Mathematical Expression Omitted].

The intermediate input equations (20), consumer demand equations (33), and investment demand equations (34) are combined into the balancing equations (35) to obtain the following output equations (36) of the model:

[Mathematical Expression Omitted]

where

[Mathematical Expression Omitted].

The matrix form of the output equations is:

x = [(I - A).sup.-1]f (38)

where

x = an nm component vector of [Mathematical Expression Omitted];

A = an nm by nm matrix of [Mathematical Expression Omitted];

I = an nm by nm identity matrix;

f = an nm component vector of [Mathematical Expression Omitted].

Given values of [Mathematical Expression Omitted], [Mathematical Expression Omitted], [Mathematical Expression Omitted], and [Mathematical Expression Omitted], the outputs of all regions are determined by (38). Using these producer prices ([Mathematical Expression Omitted]), primary input prices, ([Mathematical Expression Omitted]), trade cost factors ([Mathematical Expression Omitted]), and industrial outputs ([Mathematical Expression Omitted]), the model determines the remaining variables. The equations (20) and (21) determine the profit maximizing intermediate inputs, ([Mathematical Expression Omitted]), and primary inputs ([Mathematical Expression Omitted]). The consumption demands [Mathematical Expression Omitted], investment demands [Mathematical Expression Omitted], and trade flows [Mathematical Expression Omitted] are determined by the equations (33), (34), and (39) respectively.

Trade Flow Equations

[Mathematical Expression Omitted]

Import [Mathematical Expression Omitted] and Export [Mathematical Expression Omitted] equations are derived by summing (39) over s and r except for the shipment to its own country.

[Mathematical Expression Omitted]

[Mathematical Expression Omitted]

Price Effects of Final Demand

However, it is possible that the profit maximizing primary input demands may exceed the availability of the resource in the country when the increase in final demand uses up all the available resources in the country.

[Mathematical Expression Omitted]

In this resource constrained case, the primary input prices will go up.

[Mathematical Expression Omitted]

Note that [Mathematical Expression Omitted] is the equilibrium price of the resource [Mathematical Expression Omitted] which balance its supply with the profit maximizing demands for the resources. The [Mathematical Expression Omitted] which is assumed to be constant is the ratio of [Mathematical Expression Omitted] to [Mathematical Expression Omitted]. If the demands for the resource exceed its supply as shown in the equations (42), the resource price [Mathematical Expression Omitted] will rise until the demands for the resource are shrunk to the available level in the country.

This increase in primary input prices will increase the prices of all industrial outputs by the equations (31) and will change the input-output ratios [Mathematical Expression Omitted] by the relations (37). Therefore, under this model, it is possible to trace the price effect of final demand change as well as the input-output ratio effect of the final demand. It is a feature which conventional input-output models fail to capture.

IV. Labor Simulation Model

Labor disputes enter the model by the wage hike over productivity increase. The CES version of the MIL model developed in section III is used to trace the import and export effects resulting from the wage hike. The first primary input [Mathematical Expression Omitted] is labor input and [Mathematical Expression Omitted] is the wage rate of industry j in country r. In order to alleviate data gathering efforts and in order to simplify the computation of this model, we use an index system to describe the variables of the MIL model.

Consider an example that annually, an industry j in country r employs 2 million hours of labor services at $8 per hour as wage rate before the labor dispute occurs in the industry. Under the index system, the [Mathematical Expression Omitted] and the [Mathematical Expression Omitted] become one and $16 million respectively. We further assume that a labor dispute of this industry causes a 50% labor hour loss (i.e., 1 million hour loss) and a 50% wage hike (i.e., $12 per hour) without any increase in labor productivity. After the labor dispute, the [Mathematical Expression Omitted] and the [Mathematical Expression Omitted] become 1.5 and $8 million respectively. Notice that the product of 1.5 and $8 million become $12 million (= $12 x 1 million hours). The use of this index system alleviates data gathering efforts because it doesn't require to collect wage rates and working hours of each industry before and after the labor disputes. It only requires the values of wage payment before labor dispute with the percentage of wage hike and the percentage of working hour loss. The input-output transaction table compiled for this study provides the values of wage payments. The percentage of wage hike and working hour loss should be gathered from other sources.

To evaluate the price effect of wage hike, we take a total differentiation of (30) and evaluated the results at the index system described above (i.e., [Mathematical Expression Omitted]). The following result is obtained:

[Mathematical Expression Omitted]

Note that when the elasticity of substitution between a pair of inputs is one, equation (44) reduces to the Linear Logarithmic differential price frontiers in Liew and Liew [9, Equation 26].

The matrix form of (44) is:

d ln p = [(I - S).sup.-1] [[Omega]d ln d + [summation over k] [[Beta]*.sub.k]d ln [w.sub.k]](45)

where

S = an nm by nm matrix of [Mathematical Expression Omitted];

[Omega] = an nm by nmm matrix of [Mathematical Expression Omitted];

d ln p = an nm-component vector of the derivative of ln [Mathematical Expression Omitted];

d ln d = an nmm-component vector of the derivative of ln [Mathematical Expression Omitted];

[[Beta]*.sub.k] = an nm-component diagonal matrix of [Mathematical Expression Omitted];

d ln [w.sub.k] = an nm-component vector of the derivative of ln [Mathematical Expression Omitted].

Since we are evaluating the wage effect on prices with given trade cost factors and given other primary input prices (i.e., d ln d = 0 and d ln [w.sub.k] = 0 except k = 1 for the labor disputed country), the equation (45) becomes:

[Mathematical Expression Omitted]

Next, to compute the output effects of wage hike, we take a total differentiation of (38). The following result is obtained:

dx = [(I - A).sup.-1] dAx + [(I -A).sup.-1] df.(47)

The dA is an nm by nm matrix of [Mathematical Expression Omitted] which is obtained by taking a total differentiation of [Mathematical Expression Omitted] in (37), and by evaluating it at the index system described above (i.e., [Mathematical Expression Omitted].

The results are:

[Mathematical Expression Omitted]

where

[Mathematical Expression Omitted];

[Mathematical Expression Omitted];

[Mathematical Expression Omitted];

[Mathematical Expression Omitted];

[Mathematical Expression Omitted]

We assume that the wage hike does not affect other final demands (i.e., df = 0). Then, the output effects dx of wage hike can be obtained by (49):

dx = [(I - A).sup.-1] dAx(49)

where dx = an nm component vector of [Mathematical Expression Omitted].

The MIL model defines the value of commodity i shipped from country s to r [Mathematical Expression Omitted] as follows:

[Mathematical Expression Omitted]

where

[Mathematical Expression Omitted]

Equation (50) is the trade flow equation (39) defined in section III and equation (51) is derived from equations (35) and (36). A derivative of natural logarithmic transformation of (50) yields the following equations:

[Mathematical Expression Omitted]

Under the MIL model, the first primary input [Mathematical Expression Omitted] is labor. Therefore, we evaluate the effect of wage hike over labor productivity [Mathematical Expression Omitted] on trade cost factors [Mathematical Expression Omitted], on the prices of all products [Mathematical Expression Omitted], and on the trade quantities [Mathematical Expression Omitted].

The trade cost factor [Mathematical Expression Omitted] is composed of the transportation cost of delivering commodity i from country s to r, the cost variation due to the change in exchange rate between trading countries, and other factors such as tariffs and subsidies imposed on commodity i of country s by country r. We assume that the wage hike by the labor disputes is independent of this trade cost factor. Therefore, d ln [Mathematical Expression Omitted] is assumed to be zero.

Next, we evaluate the wage hike effect on the quantity indices of trade flows [Mathematical Expression Omitted]. By taking a derivative of (51), we obtain the following results:

[Mathematical Expression Omitted]

The wage hike due to the labor disputes does not affect other final demands [Mathematical Expression Omitted] and this term vanishes in (53). The import effect of the product i in country [Mathematical Expression Omitted] by the labor disputes is computed by (54).

[Mathematical Expression Omitted]

Similarly, export effect of the product i in country [Mathematical Expression Omitted] by the labor disputes is computed by (55).

[Mathematical Expression Omitted]

The percentage change in trade flow quantity [Mathematical Expression Omitted] is computed by dividing [Mathematical Expression Omitted] by

the target year [Mathematical Expression Omitted]

V. Data Used For the Study and Empirical Findings

Input Data

This study requires two sets of input parameters, both of which are computed from 1984 OECD trade tapes, 1983 Japan Input-Output Transaction tapes, 1983 Korea Input-Output Transaction tapes, and 1977 United States Input-Output Transaction tapes. These Japanese, Korean, and United States transaction tables, and OECD trade statistics were aggregated into a 44-sector version of 1983 Multicountry International Transaction table, which is the basic table for the study. From this table, input elasticity matrix (S), MIL coefficient matrix (A), and other supporting data are computed. Korea enters the model as a trading partner to Japan and the United States. Ballard et al. [1] showed that the elasticities of substitution between inputs are one for most U.S. industries. Since we could not gather the elasticities of substitution between inputs for Japanese and Korean industries, the unitary elasticities of substitution for all industries (Cobb-Douglas function) are used in this empirical part under the assumption that the industrial structures of Japan and Korea are similar to those of the United States.

Korean Wage Hike

Korean labor disputes reached a peak in 1987, and slowed gradually down in 1988 and 1989. We select the year 1988 as the target year of the labor simulation for this study.

The industrial outputs of Korea, Japan, and the United States have been updated to 1988 level from their base years (1983 for Korea, 1983 for Japan, and 1977 for the United States) by using the annual industrial growth rates computed from two different year input-output transaction tables. For example, the growth rates of Korean industries are computed by the information in the 1980 and 1986 Korean input-output transaction tables. Similarly, the industrial growth rates of Japan and those of the United States are computed from the 1980 and 1985 Japanese input-output transaction tables and from the 1982 and 1985 United States input-output transaction tables respectively. Table II provides the nominal industrial growth rates of Korea, Japan, and the United States. TABULAR DATA OMITTED In 1988, the Korean industrial wage hike and productivity increase are also as shown in the Table III. Also, Table VII shows industrial outputs of Korea, Japan and the United States.

The wage hike over the productivity improvement enters the MIL model in order to evaluate the price effects, industrial effects, and trade effects of Korea, Japan, and the United States.

Price Effects

Table IV provides the price effects of Korean wage hike. The 1988 Korean wage hike produces strong inflationary effects on mining industries (Nonmetallic Minerals (5.96%), Coals (4.73%), and Iron and Ferroalloy Ore (3.99%)). They are followed by manufacturing industries (General Industrial Machinery (3.04%), Transportation Equipment (2.99%), Medical and Optical (2.96%), Miscellaneous Manufacturing (2.76%), Textile Fabrics (2.47%), and Electrical Equipment (2.31%)).

Textile, Electrical Equipment, Miscellaneous Manufacturing, and Transportation Equipment are the key exporting industries of Korea. The rising prices of these exporting industries produce strong recession effects which will be further discussed in the output effect section.

In general, Agriculture, Fishery, and Service are among the least price affected industries by the 1988 Korean wage hike. The Forestry Product is the least price affected industry (0.0517%). It is followed by Grains, Crops, and Fruits (0.0724%), Polished Grains (0.1203%), Tobacco Products (0.1828%), Livestocks (0.1882%), Real Estate (0.2617%), and Wholesale and Retail Trade (0.2930%). Electricity and Gas Service is the only industry which experiences the declining price effects because the wage hike of the industry is below its productivity increase.

As expected, the Korean wage hike provides a negligible effects on the price structures of the United States economy and a very small effect on Japanese industrial prices. The strongest price effect is realized in Leather and Leather Product industry of Japan (0.2525%). It is followed by Medical and Optical (0.1411%), Electrical Equipments (0.1354%), Iron and Steel (0.1175%), and Textile Fabrics (0.1156%) of Japan.
Table II. Nominal Annual Industrial Growth Rates (Unit: Percentage)

INDUSTRY KOREA JAPAN THE U.S.

1. Grains, Crops & Fruits 9.32 1.59 -0.46
2. Livestock, Sericulture 12.66 1.59 -0.05
3. Forestry Products 7.53 1.59 1.90
4. Fishery Products 9.70 1.59 1.90
5. Coals 9.93 -5.02 -1.44
6. Iron, Ferroalloy Ore -0.55 -5.02 -4.40
7. Nonmetallic Minerals 10.50 -5.02 -3.69
8. Seafood Processing 17.55 5.38 1.93
9. Polished Grains 5.42 5.38 1.93
10. Other Food & Kindred 12.41 5.38 1.93
11. Beverages 8.23 5.38 1.93
12. Tobacco Products 8.52 5.38 4.74
13. Fiber Yarn 8.06 2.19 2.75
14. Textile Fabrics 11.92 2.19 2.13
15. Leather & Leather Products 10.42 2.19 -3.00
16. Lumber & Wood Products 5.68 -0.77 5.96
17. Pulp & Paper 13.99 -0.77 4.02
18. Printing & Publishing 14.74 -0.77 6.69
19. Basic Chemicals & Fertilizers 10.95 2.60 4.54
20. Drugs, Cosmetics and Others 12.49 2.60 4.78
21. Petroleum Refining 5.09 -1.77 -3.09
22. Rubber Products 14.78 4.51 6.29
23. Non-Metallic Mineral Products 11.08 -37.87 5.00
24. Iron & Steel Products 10.88 -1.05 1.63
25. Primary Nonferrous Metal 14.04 -2.47 0.67
26. Fabricated Metal 17.23 2.15 4.62
27. General Industrial Machinery 22.01 5.40 4.14
28. Electrical Equipment 18.13 9.14 6.74
29. Transportation Equipment 20.28 4.81 9.68
30. Medical, Optical & Other Instruments 13.48 3.20 4.06
31. Miscellaneous Manufacturing 15.13 4.51 -0.62
32. Building Construction 9.03 0.23 6.16
33. Public Works 12.24 0.23 6.16
34. Electric & Gas Services 11.87 4.96 1.59
35. Water Services 19.45 7.88 1.59
36. Wholesale & Retail Trade 11.74 2.86 6.68
37. Transportation & Warehousing 10.19 -0.06 2.74
38. Communication 18.80 4.90 4.96
39. Finance & Insurance 12.86 7.00 7.88
40. Real Estate 15.88 4.94 6.70
41. Public Administration 11.27 4.18 7.62
42. Restaurant & Hotel 35.44 7.15 7.08
43. Other Services 28.76 5.50 7.51
44. Dummy Sector 11.66 -2.75 4.31
AVERAGE 12.97 1.48 3.27


TABULAR DATA OMITTED

Industrial Effects

The 1988 Korean wage hike reduces Korean industrial outputs by $3,922 million while stimulating the United States industrial outputs by $2,171 million and the Japan industrial outputs by $240 million.

The wage hike causes price hikes of most Korean industrial outputs. Korean products become relatively more expensive than those of Japan or the United States. There will be import substitutes for Japan and United States products for Korean products. Because of the lesser demands for Korean products, the Korean economy loses its industrial outputs. The United States industries gain more than Japanese industries do because the price effects of the United States products is much smaller than those of Japanese products. For this reason, the Korean wage hike creates more demands for the United States products than for the Japanese products. Table V shows industrial effects of Korean wage hike.

The biggest loser in the Korean wage hike is the Electrical Equipment industry with $703 million output loss, which is followed by Textile Fabrics (-$399 million), Iron and Steel (-$346 million), Dummy Sector (-$295 million), Miscellaneous Manufacturing (-$210 million), General Industrial Machinery (-$181 million), and Transportation Equipments (-$175 million).

The Electricity and Gas Service which had higher productivity gain over the wage increase experience an output gain of $26.79 million. Public Works, Tobacco, and Real Estate industries had small output gains of $1.65 million, $1.31 million, and $0.45 million respectively.

The Korean wage hike produces a mixed effect on Japanese industries. The largest gainer of the Japanese industry is Wholesale and Retail Trade with $112.9 million output gains. Other gainers of Japanese industries are Real Estate ($34.01 million), Other Service ($61.79 million), Restaurant and Hotel ($33.32 million), Transportation and Warehousing ($30.68 million), and Other Food and Kindred Products ($26.64 million).
Table IV. The Price Effects of 1988 Korean Wage Hike (Unit: Percentage)

INDUSTRY KOREA JAPAN THE U.S.

1. Grains, Crops & Fruits 0.0724 0.0248 0.0010
2. Livestock, Sericulture 0.1882 0.0161 0.0012
3. Forestry Products 0.0517 0.0808 0.0014
4. Fishery Products 0.2218 0.0609 0.0025
5. Coals 4.7253 0.0801 0.0013
6. Iron, Ferroalloy Ore 3.9889 0.0391 0.0019
7. Nonmetallic Minerals 5.9652 0.0328 0.0008
8. Seafood Processing 0.4270 0.0398 0.0018
9. Polished Grains 0.1203 0.0072 0.0016
10. Other Food & Kindred 0.3576 0.0205 0.0015
11. Beverages 0.2711 0.0250 0.0019
12. Tobacco Products 0.1828 0.0221 0.0008
13. Fiber Yarn 1.0341 0.0214 0.0021
14. Textile Fabrics 2.4681 0.1157 0.0115
15. Leather & Leather Products 2.1458 0.2525 0.0244
16. Lumber & Wood Products 0.9852 0.0194 0.0021
17. Pulp & Paper 0.9370 0.0192 0.0022
18. Printing & Publishing 1.6157 0.0393 0.0014
19. Basic Chemicals & Fertilizers 0.4431 0.0439 0.0018
20. Drugs, Cosmetics & Others 0.4496 0.0259 0.0017
21. Petroleum Refining 0.3689 0.0748 0.0009
22. Rubber Products 0.8086 0.0440 0.0032
23. Non-Metallic Mineral Products 1.4083 0.0540 0.0019
24. Iron & Steel Products 1.4758 0.1175 0.0052
25. Primary Nonferrous Metal 1.5013 0.0237 0.0029
26. Fabricated Metal 1.0200 0.0961 0.0051
27. General Industrial Machinery 3.0409 0.1072 0.0044
28. Electrical Equipment 2.3135 0.1354 0.0050
29. Transportation Equipment 2.9891 0.0777 0.0056
30. Medical, Optical & Other Instruments 2.9575 0.1411 0.0033
31. Miscellaneous Manufacturing 2.7655 0.0838 0.0051
32. Building Construction 1.5875 0.0809 0.0031
33. Public Works & Other 1.3381 0.0976 0.0027
34. Electric & Gas Services -0.2297 0.0644 0.0006
35. Water Services 0.4865 0.0537 0.0014
36. Wholesale & Retail Trade 0.2930 0.0223 0.0005
37. Transportation & Warehousing 1.5356 0.0147 0.0010
38. Communication 0.4093 0.0617 0.0010
39. Finance & Insurance 0.6736 0.0496 0.0005
40. Real Estate 0.2617 0.0429 0.0003
41. Public Administration 1.7301 0.0239 0.0013
42. Restaurant & Hotel 0.6137 0.0421 0.0011
43. Other Services 0.9521 0.0277 0.0013
44. Dummy Sector 0.6030 0.1080 0.0000

Table V. Industrial Effects of 1988 Korean Wage Hike (Unit: Million Dollars)

INDUSTRY KOREA JAPAN THE U.S.

1. Grains, Crops & Fruits -10.84 5.50 68.66
2. Livestock, Sericulture -20.22 6.01 37.57
3. Forestry Products -0.04 -0.09 9.17
4. Fishery Products -11.05 0.02 3.42
5. Coals -53.73 -0.01 8.27
6. Iron, Ferroalloy Ore -16.56 -0.04 8.86
7. Nonmetallic Minerals -157.38 0.07 29.34
8. Seafood Processing -3.88 2.33 2.24
9. Polished Grains -14.04 10.72 3.52
10. Other Food & Kindred -117.99 26.64 101.69
11. Beverages -46.33 7.11 14.10
12. Tobacco Products 1.31 5.17 6.68
13. Fiber Yarn -71.30 -0.88 12.41
14. Textile Fabrics -399.38 -7.94 22.16
15. Leather & Leather Products -90.77 -43.32 1.54
16. Lumber & Wood Products -15.89 2.55 47.08
17. Pulp & Paper -66.91 3.46 34.89
18. Printing & Publishing -58.61 4.49 18.52
19. Basic Chemicals & Fertilizers -67.91 -3.46 57.73
20. Drugs, Cosmetics & Others -51.39 4.26 70.23
21. Petroleum Refining -32.93 -2.57 49.43
22. Rubber Products -17.19 1.21 27.72
23. Non-Metallic Mineral Products -74.19 0.95 17.10
24. Iron & Steel Products -346.58 -11.89 36.78
25. Primary Nonferrous Metal -70.50 -2.08 55.56
26. Fabricated Metal -45.13 -1.85 44.72
27. General Industrial Machinery -181.35 18.88 113.62
28. Electrical Equipment -703.33 -31.76 109.60
29. Transportation Equipment -85.77 -3.94 69.85
30. Medical, Optical & Other Instruments -106.17 -11.15 16.51
31. Miscellaneous Manufacturing -210.37 -3.11 17.52
32. Building Construction -27.80 -4.26 27.52
33. Public Works & Other 1.65 -0.26 9.69
34. Electric & Gas Services 26.79 -0.27 69.06
35. Water Services -2.86 0.94 3.61
36. Wholesale & Retail Trade -58.39 112.92 209.11
37. Transportation & Warehousing -175.19 30.68 64.98
38. Communication -5.68 1.02 34.25
39. Finance & Insurance -41.56 7.87 74.19
40. Real Estate 0.45 34.01 160.78
41. Public Administration -1.33 1.18 3.52
42. Restaurant & Hotel -35.28 33.32 84.75
43. Other Services -161.79 61.79 203.30
44. Dummy Sector -295.09 -14.04 110.20

TOTAL -3,922.51 240.21 2,171.45


The biggest loser in Japanese industry is Leather and Leather Products (-$43.32 million), which is followed by Electrical Equipment (-$31.76 million), Dummy Sector (-$14.04 million), Iron and Steel (-$11.89 million), and Medical and Optical (-$11.15 million).

All United States industries experience output gains by the Korean wage hike. Prime gainers of the U.S. industries are Wholesale and Retail Trade ($209.11 million), Other Services ($203.3 million), Real Estate ($160.78 million), General Industrial Machinery ($113.62 million), Dummy Sector ($110.2 million), Electrical Equipment ($109.60 million), and Other Food and Kindred Products ($101.69 million).

Trade Effects

As described earlier, the Korean wage hike causes the Korean products to be more expensive than the United States and Japanese products. The declining demands for the Korean products by all buyers in trading countries cause Korean export to fall. Korean export to Japan falls by $1,528 million whereas Korean export to the United States decreases by $282 million.

Traditionally, Korea supplies more intermediate goods than consumer goods for Japan whereas Korea exports more consumption goods than intermediate products for the United States economy. The rising prices of Korean goods cause Japanese industries to purchase their intermediate goods more from the United States or other countries than from Korea. Table VI provides the trade effect of Korean wage hike. The labor disputes decrease Japanese demands for Korean Electronic Equipments by $397.48 million. Other heavy losers of Korean industries by the reduced Japanese demands are Dummy Sector (-$267.78 million), Textile Fabrics (-$183.83 million), Iron and Steel (-$143.14 million), Miscellaneous Manufacturing (-$131.56 million), and Non-metallic Minerals (-$99.35 million). The prime losers of Korean industries in the United States markets are Electrical Equipment (-$62.82 million), General Industrial Machinery (-$39.94 million), Other Food and Kindred Products (-$31.95 million), Medical and Optical (-$28.32 million), Textile Fabrics (-$23.89 million), Transportation Equipments (-$20.65 million), and Miscellaneous Manufacturing (-$20.53 million).

The economic effect of the Korean wage hike on import structure consists of two effects. One is the import decrease because of the decrease in outputs. As the demands for outputs decrease, there are lesser input demands for foreign goods. Another is the import increase by industries to substitute lesser expensive foreign goods for relatively more expensive Korean products. These two effects are combined to determine the import effect.

As expected, there has not been much change in import demand in spite of the strong recessionary effect on Korean economy from the wage hike. The Korean import demand has decreased only $17.2 million from the U.S. and $12.71 million from Japan.

It is interesting to note that the Korean import demands for General Industrial Machinery and Transportation Equipment have gone up by $10.76 million and $6.24 million from the U.S. and by $23.08 million and $3.15 million from Japan because of the strong price effects.

VI. Conclusion

In the past, the relatively cheap, high quality, and cooperative Korean labor force was the key contributor to Korea's success of the export based growth strategy. With political liberalization, Korean labor started demanding higher wages.
Table VI. The Trade Effect of 1988 Korean Wage Hike (Unit: Million Dollars)

 KOREA - U.S. KOREA - JAPAN
INDUSTRY IMPORT EXPORT IMPORT
EXPORT

1. Grains, Crops & Fruits -7.73 -1.34 -0.01
-0.66 2. Livestock, Sericulture -0.11 -0.37 -0.05
 -0.22 3. Forestry Products 0.00 0.00 0.00
 0.00 4. Fishery Products 0.09 -1.93
0.10 -9.07 5. Coals 0.00 0.00
 0.00 0.00 6. Iron, Ferroalloy Ore -2.56 -0.02
 -0.19 -7.13 7. Nonmetallic Minerals 0.40
-3.01 0.14 -99.35 8. Seafood Processing 0.00
 0.00 0.00 0.00 9. Polished Grains -0.02
 -2.26 0.00 0.00 10. Other Food & Kindred
-3.68 -31.95 -0.15 -6.00 11. Beverages
 -0.92 -1.12 -0.23 -0.47 12. Tobacco Products
 0.03 -0.06 0.00 -0.01 13. Fiber Yarn
 -0.07 -0.25 -0.90 -4.68 14. Textile Fabrics
 0.58 -23.89 -0.89 -183.83 15. Leather & Leather Products
 -2.95 -3.62 -1.97 -50.62 16. Lumber & Wood Products
 0.02 -0.44 0.00 -4.71 17. Pulp & Paper
 -2.53 -2.32 -0.58 -1.21 18. Printing & Publishing
 0.05 -3.16 0.15 -8.21 19. Basic Chemicals &
Fertilizers -2.74 -2.44 -4.19 -2.73 20. Drugs,
Cosmetics & Others -0.23 -2.33 -0.87 -12.79 21.
Petroleum Refining 0.00 0.00 0.00 0.00
22. Rubber Products 0.16 -2.84 0.47
-8.45 23. Non-Metallic Mineral Products -0.21 -2.71 -1.44
 -34.06 24. Iron & Steel Products 0.00 -13.51 -2.25
 -143.14 25. Primary Nonferrous Metal -1.01 -0.35
-2.44 -18.34 26. Fabricated Metal 1.92 -8.16
 3.48 -19.29 27. General Industrial Machinery 10.76
-39.94 23.08 -61.01 28. Electrical Equipment -8.25
 -62.82 -16.96 -397.48 29. Transportation Equipment
6.24 -20.65 3.15 -5.47 30. Medical, Optical & Other Instruments
 -3.73 -28.32 -7.28 -50.09 31. Miscellaneous Manufacturing
 -0.32 -20.53 -1.19 -131.56 32. Building Construction
 0.00 0.00 0.00 0.00 33. Public Works & Other
 0.00 0.00 0.00 0.00 34. Electric & Gas Services
 0.00 0.00 0.00 0.00 35. Water Services
 0.00 0.00 0.00 0.00 36. Wholesale & Retail Trade
 0.00 0.00 0.00 0.00 37. Transportation &
Warehousing 0.00 0.00 0.00 0.00 38. Communication
 0.00 0.00 0.00 0.00 39. Finance &
Insurance 0.00 0.00 0.00 0.00 40. Real
Estate 0.00 0.00 0.00 0.00
41. Public Administration 0.00 0.00 0.00
0.00 42. Restaurant & Hotel 0.00 0.00 0.00
 0.00 43. Other Services 0.00 0.00 0.00
 0.00 44. Dummy Sector -0.37 -1.84 -1.69
 -267.78

TOTAL -17.20 -282.17 -12.71
-1528.36
Table VII. Industrial Output in 1988 U.S. Dollars (Millions)

INDUSTRY KOREA JAPAN THE
U.S.

1. Grains, Crops & Fruits 14625.57 40227.28
61836.70 2. Livestock, Sericulture 6790.38 17236.93
 54938.16 3. Forestry Products 1322.21 6309.72
 9623.82 4. Fishery Products 2831.13
12964.09 1866.33 5. Coals 1138.71
 930.13 14208.90 6. Iron, Ferroalloy Ore 85.10
 358.80 3302.26 7. Nonmetallic Minerals
945.91 6096.31 35899.66 8. Seafood Processing
 2214.21 14643.94 5436.57 9. Polished Grains
 7425.69 21483.74 9947.30 10. Other Food & Kindred
 14081.76 90581.50 174819.45 11. Beverages
 2495.71 28400.84 30185.19 12. Tobacco Products
 2582.66 14691.23 21642.94 13. Fiber Yarn
 5018.38 2258.80 39045.69 14. Textile Fabrics
 14754.39 36675.24 73833.38 15. Leather & Leather
Products 2665.73 22119.63 5502.78 16. Lumber & Wood
Products 2139.36 25417.35 95739.93 17. Pulp &
Paper 4400.98 31821.20 80170.00 18.
Printing & Publishing 2661.99 31613.86 104289.20
19. Basic Chemicals & Fertilizers 9716.04 7941.32
115806.89 20. Drugs, Cosmetics & Others 8914.14 71967.85
 71749.36 21. Petroleum Refining 12944.04 79242.10
 70418.23 22. Rubber Products 3446.31
15263.78 78628.93 23. Non-Metallic Mineral Products 5868.59
 5145.99 59823.83 24. Iron & Steel Products 13944.57
 103044.10 77984.95 25. Primary Nonferrous Metal
2574.71 18116.17 44528.23 26. Fabricated Metal
 7714.93 56368.68 145920.74 27. General Industrial Machinery
 11689.98 149542.12 189479.58 28. Electrical Equipment
 20015.81 226772.15 186770.99 29. Transportation Equipment
 14231.13 157700.50 498430.58 30. Medical, Optical & Other
Instruments 1115.17 18315.97 39168.37 31. Miscellaneous
Manufacturing 4149.49 52280.27 18441.87 32. Building
Construction 14748.96 136827.10 342386.44 33. Public
Works & Other 11146.51 88959.28 178053.57 34.
Electric & Gas Services 7972.29 73152.27 124438.55
35. Water Services 917.23 27509.07
1402.18 36. Wholesale & Retail Trade 21668.46 283758.68
801182.03 37. Transportation & Warehousing 16941.19 97542.07
 170533.99 38. Communication 4654.66 28274.31
 128154.15 39. Finance & Insurance 6523.44
120124.67 307358.16 40. Real Estate 10539.55
 169610.30 576528.48 41. Public Administration
12433.57 81935.34 68413.91 42. Restaurant & Hotel
 39586.73 229109.37 353079.70 43. Other Services
 31189.06 269220.61 759494.82 44. Dummy Sector
 6147.09 47041.79 344973.96

TOTAL 388972.50 3018588.00
6575426.00


This paper investigates the effects of the wage hike on Korea's trade with Japan and the United States. The empirical results show that there is a substantial decrease in export to Japan and a mild reduction in export to the United States with a minimal decrease in import from Japan and the United States, thus causing further trading imbalance against Korea.

Heavy losers from the Korean labor disputes are Electronic Equipments, Textile Fabrics, Iron and Steel, Miscellaneous Manufacturing, and Non-metallic Minerals. These are also the key export industries of Korea.

1. These points were made by Korean Development Institute [5].

2. In the study of Ballard et al. [1], a simple t-test supports the acceptance of the hypothesis that the true elasticity of substitution between inputs is one for most of U.S. industries.

3. To simplify the presentation, we use the following conventions. [Mathematical Expression Omitted]. For example, f([x.sub.1] . . . [x.sub.n]) can be expressed as f([x.sub.i](i = 1 . . . n)) or f([x.sub.i](i)).

4. [[Sigma].sub.s][is not equal to]r indicates that the subscript s is summed from 1 to m except the s equals the subscript r.

5. For a single region CES price frontier consult Liew and Liew [7].

References

1. Ballard, Charles, Don Fullerton, John Shoven and John Whalley. General Equilibrium Analysis of U.S. Tax Policies. Chicago: University of Chicago Press, 1985.

2. Christensen, Laurits, Dale Jorgenson and Lawrence Lau, "Transcendental Logarithmic Production Frontiers." The Review of Economics and Statistics, Volume 55, February 1973, 28-45.

3. Hewings, Geoffrey and Richard Jensen. "Regional, Interregional and Multiregional Input-Output Analysis," in Handbook of Regional and Urban Economics, Volume 1, edited by P. Nijkamp. Amsterdam: North-Holland Publishing Company, 1986, pp. 295-355.

4. Jorgenson, Dale. "Econometric Methods For Applied General Equilibrium Analysis," in Applied General Equilibrium Analysis edited by Scarf, Herbert and John Shoven. Cambridge: Cambridge University Press, 1984, pp. 139-203.

5. Korean Development Institute. "Korean Labor Relationship," K.D.I. Report, 1988.

6. Leontief, Wassily and Alan Strout. "Multiregional Input-Output Analysis," in Structural Interdependence and Economic Development. edited by T. Barna. New York: St. Martin's Press, Inc., 1963.

7. Liew, Chong Kiew and Chung Ja Liew. "Energy Simulation With A Variable
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Author:Cho, Joonmo
Publication:Southern Economic Journal
Date:Oct 1, 1994
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